Field of the Invention
This invention relates generally to system and method for determining bias and misalignment errors in the outputs from a 6-degree of freedom (DOF) inertial measurement unit (IMU) and, more particularly, to a system and method for determining bias and misalignment errors in the outputs from a 6-DOF IMU on a vehicle using velocity and attitude data from a global navigation satellite system (GNSS) and/or an inertial navigation system (INS), where the method includes determining an ideal acceleration estimation and an ideal angle rate estimation in a vehicle frame using the velocity and attitude data, and determining an IMU bias error and a misalignment error using the ideal acceleration and angular rate estimation and the measured angle rate and acceleration outputs from the IMU.
Discussion of the Related Art
The operation of modern vehicles is becoming more autonomous, i.e., vehicles are able to provide driving control with less driver intervention. Cruise control systems have been on vehicles for a number of years where the vehicle operator can set a particular speed of the vehicle, and the vehicle will maintain that speed without the driver operating the throttle. Adaptive cruise control systems have been recently developed in the art where not only does the system maintain the set speed, but also will automatically slow the vehicle down in the event that a slower moving preceding vehicle is detected using various sensors, such as radar and cameras. Certain modern vehicles also provide autonomous parking where the vehicle will automatically provide the steering control for parking the vehicle. Some vehicle systems providing automatic braking without driver intervention to avoid rear-end collisions. As vehicle systems improve, they will become more autonomous with the goal being a completely autonomously driven vehicle. For example, future vehicles probably will employ autonomous systems for lane changing, passing, turns away from traffic, turns into traffic, etc.
Various active safety control systems, driver assist systems and autonomous driving operations on vehicles, such as systems providing electronic stability control (ECS), adaptive cruise control (ACC), lane keeping (LK), lane changing (LC), etc., require highly robust and precise modules for estimating various vehicle dynamics. Such modules are necessary to provide knowledge of the vehicle position and velocity to control the vehicle.
Active safety control for the systems discussed above, and others, rely on accurate vehicle speed estimation for proper performance. Currently, these types of proposed systems rely on wheel speed sensors and other vehicle kinematic inputs to provide the vehicle speed estimation. However, sometimes sensors and control modules that determine vehicle speed fail or operate improperly, where loss of vehicle speed could be serious. Certain automotive safety requirements, such as ASIL-D, require redundant vehicle speed estimation processes in the event the primary estimation processor fails. For example, for those systems that require active control, the control systems are required to provide accurate speed estimation for five seconds after the failure event so as to give the driver time to take control of the vehicle.
It is known in the art to provide a 6-DOF IMU on a vehicle that provides six rate of change measurements, particularly, angular rate measurements of vehicle roll, pitch and yaw, and acceleration measurements of longitudinal acceleration, lateral acceleration and up/down acceleration. A typical IMU provided on a vehicle will include three gyros that provide the angular rate measurements and three accelerometers that provide the acceleration measurements.
It has been proposed in the art to use the angular rate and acceleration measurements from an IMU on a vehicle to provide signals that can be used for vehicle speed estimation. U.S. patent application Ser. No. 14/680,894, filed Apr. 7, 2015, titled, Fail Operational Vehicle Speed Estimation Through Data Fusion of 6-DOF, IMU, GPS and Radar, discloses a system and method for providing redundant vehicle speed estimation that determines whether one or more primary sensors that provide vehicle speed has failed, and if so, estimates the vehicle speed in a secondary module using a buffered vehicle speed value and inertial measurement signals from an IMU. The method also uses GPS signal data and/or velocity data provided by range sensors from static objects to improve the estimated vehicle speed if they are available.
In the process discussed in the '894 application, the accuracy of the secondary vehicle speed estimation largely depends on the accuracy of the IMU acceleration and angular rate measurements. However, the measurements of acceleration and angular rates provided by the IMU on a vehicle for this purpose usually deviate from the actual acceleration and angular rate values due to several error sources. The two major sources of error for the IMU measurements are accelerometer and gyro bias components and frame misalignment corresponding to mounting the IMU to the vehicle. There is a bias term on each axis, which corresponds to six bias error terms in addition to three misalignment errors. Although it is desirable to perfectly align the IMU with the vehicle frame, there still are mounting errors that even if they are small, could provide significant misalignment errors in the calculations. Further, the bias and misalignment errors can be improved during manufacture of the vehicle by moving the vehicle and identifying the errors. However, such error corrections of bias and misalignment are also difficult to accurately obtain. Further, these error corrections for bias and misalignment often require special vehicle maneuvers during the manufacturing stage of the vehicle, and further bias terms are not fixed and may change in time due to different road, vehicle and environment conditions.